Archive February 2012

An interesting article on predictive analysis appeared in the New York Times on 16 February. The main focus was on how the US retailer Target was using its information on customers to predict which of them were pregnant, and so send them information on pregnancy and baby-related products. Simultaneously impressive and scary. The article couldn’t find out how accurate it really was, but the company has improved its revenue stream.

Many other companies are doing the same thing, which you may be aware of if you belong to a loyalty programme, or if you shop online.

This is an example of what these days is called ‘Big Data’. It has many firms, governments and consultants very excited. McKinsey Global Institute, along with a lot of others, has been looking at the implications of ‘Big data’. The expectation is that with detailed analysis of lots of different information companies can sell you more stuff or stuff that better meets your needs, while governments can plan more effectively or efficiently, and provide services tailored for you.

This graphic illustrates where McKinsey see better use of data helping a range of sectors

You could dispute how McKinsey have characterised the ease of collection or value of big data. I for one think that current departmental silos make it hard to collate a range of government data — and it can be extremely difficult for people in the same agency to get access to even some of their own data. But that is a relatively minor quibble that will be overcome. Although, based on the past record of IT system upgrades, this seems unlikely to be as cheaply or easily achieved as the decision makers may hope.

Who wouldn’t want better health care services through better data analysis, smarter urban design through study of mobile data, or creating new businesses that make data useful? Or even reduced insurance costs because the insurance company can tell I’m being a good boy?

I can see benefits to that, but there are also plenty of challenges. I’m reminded of what my PhD adviser (take a bow David Penny [PDF]) warned me of back in the day when ‘big data’ were 500 base pairs each from about 20 species. I paraphrase but it was something like ‘it can feel nice running barefoot through the data, but it’s not much use if you can’t make sense of it’.

Technology review covers the findings of a paper by Boyd & Crawford about where having more data isn’t necessarily better. The data may not be as objective or as accurate as you assume (eg, users of social networks are generally not representative of the whole population (so far), and have biases to what they post, or don’t post).

Other issues Boyd & Crawford highlight are:

Quantity of data isn’t a substitute for quality. A UK Foresight report [PDF] notes that being able to demonstrate the authority of the data in real time will be a critical requirement in the future, particularly for government data.

All data is not equivalent. Not every connection in networks are equivalent. Frequency of contact on social networks (or mobile devices) does not necessarily mean you have identified a person’s closest friends or colleagues.

There are ethical judgements to be made when using ‘public’ information. They note that in at least one study it was demonstrated that individual privacy could be compromised from supposedly anonymised data. Since the ‘Big data’ field is new it is unclear what ethical implications may arise from aggregating information from individuals.

Finally, not everyone has the same access to large databases, so there risks of creating new digital divides and inhibiting testing of conclusions from analyses of large data sets. Researchers in some fields are incentivised and generally good at sharing their data, but others aren’t yet.

Boyd & Crawford exhort researchers to not overlook the value of ‘small data’ — what data you use depends upon the questions you have.

Leaving aside how you analyse super data sets, just the organisational and technical challenges of going from handling small to big data won’t be easy (and it’s not just a question of being cloud based). Governments and firms will also need to have real time information to inform their decisions and services, rather than just being able to analyse what happened previously.

Wired lost the plot a few years ago when it claimed that you don’t need a scientific method if you have lots of data. The Target example is a case where there is quite a clear outcome being sort, the company did have a hypothesis to test and threw strong statistical analyses at the problem. Whether such applications are acceptable uses is up for debate.

One final concern is whether we all, as members of the public and consumers, become reduced to sets of data points in cosmic analytical frameworks and suffer the tyranny of regression to the mean. Choice still matters. When buying goods online, being told what items other people also bought is inoffensive and you can choose whether you buy them too. I don’t want to go to my doctor and be told that others with most of my symptoms had treatment X, so that’s all I can have. Big data can better help identify problems and options, but they shouldn’t necessarily dictate the response.

Is 3D printing — where objects are built layer by layer (with plastics, or in some cases other materials) via something akin to an ink jet printer — ‘the future’ of manufacturing, or will it largely be the realm of hobbyists churning out useful and kitschy playthings?

At Technology Review Christopher Mims argues that the latter is more likely, although he acknowledges that 3D printing (aka additive manufacturing) will have a place in rapid prototyping within existing firms. 3D printing had a large presence at this year’s Consumer Electronics Show, with falling costs of hardware and rising numbers of ‘apps’ signalling declining barriers to designing and making your own widgets. Have a look at Thingiverse to see what DIYer’s are already printing.

Tim Maly challenges Christopher’s perspective. While agreeing that current designs and materials are on the whole fairly crappy, he takes a longer view of how this type of manufacturing will play out. Both agree there is plenty of hype at the moment.

3D printing is already entering the classrooms of some secondary schools elsewhere. There are also school competitions for 3D designs. What with robot competitions, PCR machines, and iPads in schools these days, there’s a lot more to stimulate and entice and engage future scientists and engineers.

One analysis suggests that 3D printing may find its niche in the non-mass production zone; producing items in the 10 to 10,000 unit range.

Critical factors for future wider adoption of 3D printing include faster printing, scaling up production, better design tools, the development of new materials (so high performance objects can be made) and developing standards for these materials. There is also concern brewing over intellectual property issues. Particularly, how IP law may be applied as 3D printing becomes more widely known and tries to maintain an open source ethos. If your future cell phone includes a good 3D scanner will it be OK to scan any object you come across and then go home and recreate it? How about downloading someone else’s design?

On a broader level, it is important to view 3D printing as part of the future manufacturing environment, not as the new environment. A UK Foresight report on Technology and Innovation Futures in the in 2020‘s [PDF, 0.8 MB] notes the rise of manufacturing on demand, helped in part by 3D printing. This report highlights the necessity to consider manufacturing as the provision of services as well as products. Some companies already do this (in the aeronautical sector, for example). In the future, more value may come from the service side of the manufacturing business.

The New Zealand government is keen to boost high value manufacturing. MSI’s Request for Proposals for High Value Manufacturing and Services is out. However, they are looking to invest only around $26 million a year. And this could be spread across a whole range of areas, including geothermal engineering, agricultural technologies, digital content tools, and medical devices. So a relatively small amount of the research money, even if you add in industry co-funding. How well prepared and supported will our manufacturing sector be as other economies put ever greater emphasis on new manufacturing initiatives?

One of the issue’s he highlighted was what he called a “Copernican” revolution in society, driven by economic, environmental, societal, political, technological and organisational changes. Nothing new there for seasoned futurists. Although I would dispute whether the current trends and changes are as profound as the existential implications resulting from Copernicus’ heliocentric view of the universe. And societies have been through some equally, or arguably greater, changes during the last two hundred years (think industrial and green revolutions, not to mention world wars).

But I’m not writing to quibble about analogies. Prof Benington spent some time talking about the difficulty for governments to address complex problems through the traditional hierarchical nature of government processes. He illustrated this with work he was involved with at trying to reduce alcohol and drug problems in Leicester City, and how what he calls “Polycentric Networked Governance” may be a better way of dealing with systemic problems. This is where a traditional top down hierarchical approach, where central (or local) government provide the solution, won’t work. The polycentric model is where a range of different organisations and actors need to work together to define the problem and the solution. He covers this in his book Public Value: Theory and practice.

The first time I came across “polycentric” was just last month when I referenced Elinor Ostrom in 12 trends post-Christmas (part 2). However, the concept is decades old, being applied (with various levels of success) to, for example, resource management, urban planning, security, economic issues and new technologies. The polycentric model isn’t new to New Zealand, though the name may be.

While promising, polycentric governance isn’t necessarily a replacement for good old hierarchies. Discussion at the seminar wondered how sustainable polycentric governance can be, and how meaningful accountability can be assured. Benington’s view is that hierarchical, networked and market-based governance models all have a place, we just need to be aware of when it is most appropriate to use each of them.

Internal disputes within the network, or failure to get some critical actors involved, can hamper successful polycentric governance. Europe has been a fan of a polycentric approach but they seem to be retreating from this, at least in regard to spatial planning (and undoubtedly, management of national financial accounts).

Rather than governments (and other organisations) embracing new or different ways of governing under uncertainty, there seems to be the strong temptation to maintain (or go back to) the old and familiar command and control approach, or just shifting accountability elsewhere – austere governance in a broader sense. In times of change - or revolutions – we need to think more expansively.

Futurist Thomas Frey recently blogged about a talk he gave at a TEDx event — claiming 2 billion jobs will disappear by 2030. He notes his purpose wasn’t to make the future seem bleak, but to highlight how technologies are changing the nature of work.

He looks at five ‘industries’ to illustrate the types of jobs that may be lost and the types of new ones that may be created. The five are energy, transportation, education, 3D Printers, and robots. The latter two aren’t, of course, industries. Thomas suggests that robots will replace fishermen and farmers, while new vocations in fashion designers for robots will emerge.

There is value in highlighting the changing nature of work, but these top of the head speculations irritate me. The 2 billion figure is a wild guess, and calling 3D printing an industry is just sloppy.

Sure, most economies are increasingly reliant on technologies (and robots are replacing humans in a range of roles), but it is hard to predict how they will really affect the types of jobs in the future. Imagining cute- or silly-sounding new jobs doesn’t help.

Another set of future job titles was created for the UK’s short-lived Science: So What? So everything campaign a few year ago. New careers proposed included body part makers and nano-medics. The quality of this ‘Shape of jobs to come’ report was quickly criticised. That’s part of the slippery slope of futurism – succumbing to the dark side of prediction, rather than the staying with more knightly analytical and questioning quests.

McKinsey have done a more detailed analysis of the future of work in the US in their 2011 report ‘An economy that works: job creation and America’s future’ [PDF, 2.1 MB]. The Economist also looked at the future of work. What seems likely is that the current trends for rapid growth in IT-related jobs and work requiring complex knowledge will continue. The exact nature of future jobs and work though are unclear. No one predicted the diversity of IT-related jobs that we now see.

Still, scientists, engineers, teachers, health-care practitioners, lawyers, builders, etc seem likely to be vocations 20 or 30 years from now. As the McKinsey and Economist reports discuss, the more pressing concern is how much of the potential workforce will be gainfully and productively employed, not what your job title is.

Are ‘green’ or clean tech jobs the way of the future? The Green Party [PDF] (and others) are keen on them. But the label gives the impression that the jobs will all be cool, interesting, and well paid. On the contrary, many seem likely to be mundane and poorly paid (like installing home insulation), or simply build on existing trades such as plumbers and electricians.

As I noted in a previous post, we need to plan and prepare for a broader scope of productive and attractive occupations. This including changing the way we educate and train our students and the existing work force so they (and we) are better prepared for new or more varied types of work. Just making up new future job titles isn’t enough.

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